1. Field of the Invention
The present invention relates to an adaptive equalizer for performing partial response (PR) equalization on a waveform reproduced by an optical recording apparatus or magnetic recording apparatus, to a decoding device using the adaptive equalization, and to an error detecting device.
2. Description of the Related Art
Conventionally, an adaptive equalizer for performing adaptive equalization using a least mean square (LMS) algorithm has been known.
An FDTS/DFE, that is, a decision feedback equalizer (DFE) that uses fixed delay tree search (FDTS) as signal-determining means, is also known from Jeakyun Moon, “Performance Comparison of Detection Methods in Magnetic Recording”, IEEE Transaction on Magnetics, Vol. 26, No. 6.
Noise predictive maximum likelihood (NPML), which improves detection performance by whitening noise increased during PR equalization, is also know from E. Eleftheriou, “Noise-Predictive Maximum-Likelihood (NPML) Detection for the Magnetic Recording Channel” (IEEE 1996, etc.).
However, when adaptive equalization is performed using the above-noted LMS algorithm, original data must be provisionally determined from a waveform. If data having a low signal distortion and noise ratio (SDNR) and having a large amount of distortion, such as noise and equalization error, is detected with respect to a threshold to perform the provisional determination, then the determination result contains a large amount of error to make it difficult to achieve high-speed operation with an increased adaptive gain.
This can also be true for a phase locked loop (PLL), auto gain control (AGC), and so on that require a dynamic high-speed operation. That is, detecting data having a low SDNR with respect to a threshold to obtain an error signal leads to a large amount of error, thus making it difficult to achieve high-speed operation.
Even when an attempt is made to equalize an input waveform having a small-amplitude portion or having a missing portion in a frequency range required for partial response, a frequency range that cannot be equalized remains. Such error remains as an equalization error that strongly depends on the pattern of the input data. This causes the performance of a decoding device to greatly decrease, thus leading to a decrease in bit error rate (BER).
In the above-described FDTS/DFE, a feedforward filter (FFF) needs to equalize an input waveform to a waveform that satisfies causality. If precursor inter-symbol interference (ISI), i.e., the leading-edge portion of the ISI, of a waveform equalized by the FFF remains to permit a waveform that does not satisfy causality to be input to an FDTS decoder and/or a Viterbi decoder, future-data prediction, which is a basic principle of digital signal processing, cannot be achieved. Thus, waveform distortion resulting from the precursor ISI cannot be removed. Therefore, with the FDTS decoder and the Viterbi decoder, equalization error resulting from the precursor ISI leads to an increase in error rate.